Network construction type energy storage parameter adaptive control method for improving transient stability

Abstract

The invention discloses a network construction type energy storage parameter adaptive control method for improving transient stability. The method comprises the following steps: determining a rated angular frequency of a network construction type energy storage system, measuring a current operation angular frequency, and calculating an angular frequency deviation and an angular frequency change rate; the VSG output active power is measured, and the active power deviation is calculated in combination with the mechanical power instruction value; dividing a system oscillation period into four oscillation intervals; calculating a damping coefficient reference value and a rotational inertia reference value by using the maximum mechanical torque of the VSG system, the maximum angular frequency offset allowed by the system and the maximum active power output by the system; calculating real-time rotational inertia and a damping coefficient according to the oscillation interval in combination with the adjustment coefficient; and the rotational inertia and the damping coefficient controlled by the VSG are adjusted. According to the method, the defect that transient stability and dynamic response are difficult to consider by fixed parameters in traditional virtual synchronous generator control is overcome, the frequency overshoot is remarkably reduced, and the recovery time is shortened.

Description

Technical Field

[0001] This invention belongs to the field of power system stability control technology, specifically relating to an adaptive control method for grid-type energy storage parameters to improve transient stability. Background Technology

[0002] Accelerating the development and utilization of new energy sources faces grid stability issues caused by large-scale grid connection. Due to the random fluctuations and intermittent nature of new energy sources, and the low impedance and insufficient support capacity of their grid-connected equipment, a high proportion of grid connection poses a severe challenge to the operation and control of the power system. Especially in areas rich in wind and solar power resources but far from the main grid, during the transmission of high proportions of new energy, due to insufficient local reactive power support, reduced system inertia, and prolonged fault clearing time, power angle oscillations, frequency deviations, and even transient instability often occur.

[0003] The fundamental condition for stable power transmission when new energy power generation equipment is connected to the grid is to maintain synchronization with the grid. Synchronization is dominated by power electronic control, and the grid-connection performance of the converter significantly impacts system stability. Based on converter control strategies, there are two main types: grid-following (GFL) and grid-forming (GFM). Current new energy grid-connected systems primarily use grid-following converters (VSCs). VSCs achieve synchronization by following the grid voltage through a phase-locked loop (PLL) and employ current vector control of the grid-connected current to achieve rapid power regulation, appearing externally as a controlled current source. Because VSCs need to follow the grid voltage via a PLL, the AC system must provide a synchronization voltage. During grid connection, VSCs cannot provide beneficial support to the grid. As their penetration rate in the power system increases, the grid strength weakens in some areas, increasing the difficulty of grid frequency and voltage regulation. The interaction between VSCs and weak grids leads to frequent broadband oscillation accidents, which is detrimental to the safe and stable operation of high-penetration new energy power systems.

[0004] In recent years, grid-based energy storage technology has emerged as an new technology. GFM (Power Synchronization Management) utilizes power synchronization control to maintain frequency consistency with the grid, controlling AC voltage by adjusting voltage amplitude and frequency, thus exhibiting "voltage source" characteristics. It can autonomously generate the required voltage without relying on the grid, enabling independent operation and stable operation even in weak grid environments. In a grid-based energy storage system, each energy storage unit possesses autonomous control and interconnection capabilities. When the system is disturbed, it can respond quickly, actively outputting reactive power and frequency-modulated power, thereby buffering the system in the early stages of a fault and effectively suppressing power angle oscillations and stability degradation.

[0005] Currently, research on control strategies for grid-based energy storage mainly focuses on droop control and virtual synchronous machine (VSG) control strategies. Droop control establishes a linear droop relationship between active power and frequency, and reactive power and voltage, enabling autonomous power allocation among multiple energy storage units and providing basic grid support. It was the earliest engineering application of this control strategy for grid-based energy storage. However, this strategy lacks simulation of the inertial components of synchronous generators, resulting in a lack of system inertia support and difficulty in suppressing rapid fluctuations in grid frequency. VSG control, by simulating the second-order motion characteristics of synchronous machines, can effectively provide instantaneous inertia support and damping, significantly improving the grid's anti-interference capability in scenarios with high new energy penetration. It is particularly suitable for scenarios with extremely high stability requirements, such as large-scale grid inertia compensation and black-start power supplies. In engineering practice, the Jingmen Xingang grid-based energy storage power station in Hubei Province, as the first 100 MWh-level grid-based energy storage power station in China, has been successfully connected to the grid at full capacity, employing VSG control technology. The project completed over 30 performance tests, including low-voltage ride-through, inertial response, and black start, verifying the stability and support capabilities of grid-based energy storage under extreme conditions, providing a technical reference for subsequent large-scale applications. Goldwind Technology's grid-based wind and energy storage station, as the first grid-based wind and energy storage station in China to conduct a 220kV black start experiment, is equipped with 200MW grid-based wind turbines and a 36MW / 120MWh grid-based energy storage system. It successfully achieved black start and microgrid artificial short-circuit experiments in a completely off-grid state. The experiment verified the active support capability of grid-based equipment under system disturbances of varying sizes, providing an engineering demonstration for independent grid-connected new energy sources in weak grid environments.

[0006] Although virtual synchronous generator (VSG) control technology has made significant progress in simulating the characteristics of synchronous generators and supporting power system stability, its core parameter (moment of inertia) remains a challenge. and damping coefficient Optimization of VSG control still faces many challenges. Currently, most mainstream VSG controls employ fixed parameter designs, relying on offline tuning or empirical value configuration. and While it can meet the basic stability requirements under specific working conditions, it is difficult to adapt to complex and ever-changing actual operating scenarios.

[0007] Specifically, in the field of adaptive control, research on the dynamic adjustment of moment of inertia and damping coefficient still has significant shortcomings. On the one hand, existing single-parameter adaptive methods only focus on the independent adjustment of inertia or damping, failing to consider the coupling relationship between the two. For example, simply increasing the inertia can suppress frequency abrupt changes, but it will prolong the recovery time; increasing the damping alone can accelerate oscillation decay, but it may lead to an increase in steady-state deviation. This "one-sided" adjustment mode makes it difficult to achieve synergistic optimization of transient stability and dynamic response speed.

[0008] On the other hand, existing two-parameter adaptive strategies mostly rely on simplified linear models or fixed threshold-triggered adjustments, lacking a refined capture of the system's dynamic characteristics. For example, some methods adjust parameters only based on the absolute value of the frequency deviation, ignoring the influence of the frequency change rate, leading to lag in adjustment during the initial stage of disturbance (the stage of accelerated frequency change) or over-adjustment during the later stage of oscillation (the stage of decelerated frequency convergence). Furthermore, most studies do not consider the differentiated requirements for parameter adjustment ranges under different disturbance intensities (such as small load fluctuations and severe faults), resulting in insufficient support capability of the control strategy under strong disturbances or unnecessary parameter fluctuations under weak disturbances.

[0009] These research shortcomings often lead to problems such as large frequency overshoot, long recovery time, and low-frequency oscillations in traditional VSG control in power systems with high proportions of renewable energy integration and multiple superimposed disturbances. In summary, the adaptive control method for grid-connected energy storage parameters involved in this invention, which improves transient stability, can collaboratively adjust the moment of inertia and damping coefficient according to the real-time dynamic characteristics of the system (such as oscillation range and rate of change). This is of great significance for improving the robustness and adaptability of VSG under complex operating conditions. Summary of the Invention

[0010] This invention is proposed to address the problems existing in the prior art, and its purpose is to provide an adaptive control method for grid-type energy storage parameters to improve transient stability.

[0011] The technical solution of this invention is: an adaptive control method for grid-type energy storage parameters to improve transient stability, comprising the following steps: A. Determine the rated angular frequency of the grid-type energy storage system, and simultaneously measure the current operating angular frequency to calculate the angular frequency deviation and angular frequency change rate; B. Measure the active power output of the VSG and calculate the active power deviation by combining it with the mechanical power command value; C. Based on the synchronous generator's power angle curve and frequency oscillation characteristics, the system oscillation period is divided into four oscillation intervals; D. Calculate the reference values ​​for damping coefficient and moment of inertia using the maximum mechanical torque of the VSG system, the maximum allowable angular frequency offset of the system, and the maximum active power output of the system; E. Based on the oscillation range determined in step C, and in conjunction with the adjustment coefficient, calculate the real-time moment of inertia and damping coefficient; F. Adjust the rotational inertia and damping coefficient of the VSG control.

[0012] Furthermore, step A determines the rated angular frequency of the grid-type energy storage system, while simultaneously measuring the current operating angular frequency and calculating the angular frequency deviation and rate of change of angular frequency. The specific process is as follows: First, the rated angular frequency of the grid-type energy storage system is Simultaneously measure the current operating angular frequency. ; Then, calculate the angular frequency deviation. and rate of change of angular frequency ,as follows: .

[0013] Furthermore, step B measures the active power output of the VSG and, in conjunction with the mechanical power command value, calculates the active power deviation. The specific process is as follows: Measure the active power output of the VSG Combined with mechanical power command value Calculate the active power deviation ,as follows: .

[0014] Furthermore, step C divides the system oscillation period into four oscillation intervals based on the synchronous generator's power angle curve and frequency oscillation characteristics. The specific process is as follows: Firstly, in interval number ①, the active power deviation Greater than zero, angular frequency deviation Greater than zero, rate of change of angular frequency Greater than zero; Secondly, in interval number ②, the active power deviation Less than zero, angular frequency deviation Greater than zero, rate of change of angular frequency Less than zero; Thirdly, in interval number ③, the active power deviation Less than zero, angular frequency deviation Less than zero, rate of change of angular frequency Less than zero; Fourth, in interval number ④, the active power deviation Greater than zero, angular frequency deviation Less than zero, rate of change of angular frequency Greater than zero.

[0015] Furthermore, step D uses the maximum mechanical torque of the VSG system, the maximum allowable angular frequency offset of the system, and the maximum active power output of the system to calculate the reference values ​​for the damping coefficient and the moment of inertia. The specific process is as follows: First, the maximum mechanical torque of the VSG system is The maximum allowable angular frequency offset of the system is The maximum active power output by the system is ; Then, calculate the reference value of the damping coefficient. and the reference value of rotational inertia ,as follows: .

[0016] Furthermore, step E calculates the real-time moment of inertia and damping coefficient based on the oscillation range determined in step C and the adjustment coefficient. The specific process is as follows: First, the oscillation intervals defined in step C are obtained. , and This is the adjustment coefficient; Then, calculate the real-time moment of inertia. and damping coefficient ,as follows: .

[0017] Furthermore, step F adjusts the rotational inertia and damping coefficient of the VSG control, as follows: Under the proposed control method, the system angular frequency and output active power satisfy the following equation: .

[0018] Furthermore, the adaptive control method for grid-connected energy storage parameters is applicable to grid-connected energy storage systems in islanded microgrids, grid-connected microgrids, and new energy power plants.

[0019] Furthermore, the mechanical power command value in step B The given value can be directly input as a target reference value for active power control of the VSG in a grid-type energy storage system.

[0020] The beneficial effects of this invention are as follows: This invention relates to a method for dual-parameter coordinated adjustment in virtual synchronous generator control. Its core advantage lies in breaking through the performance bottleneck of traditional fixed parameter control and achieving the integration of dynamic response speed and transient stability.

[0021] This invention features fast dynamic response, high transient stability, and does not rely on a communication system, thus meeting the development requirements of new energy power systems. When the system is subjected to small disturbances, the parameters change gradually, avoiding over-adjustment; when severe disturbances occur, the parameters adjust rapidly to suppress frequency abrupt changes.

[0022] The interval division rule proposed in this invention makes parameter adjustment more targeted, optimizing the effects of inertia and damping at different oscillation stages.

[0023] This invention solves the problem in traditional virtual synchronous generator control where fixed parameters are difficult to balance transient stability and dynamic response, significantly reducing frequency overshoot and shortening recovery time. Attached Figure Description

[0024] Figure 1 The moment of inertia proposed in this invention J Adaptive control block diagram; Figure 2 The damping coefficient proposed in this invention D Adaptive control block diagram; Figure 3 A circuit model for a new energy transmission system with grid-type energy storage; Figure 4 A simplified circuit for a new energy transmission system with grid-type energy storage; Figure 5 The power angle and frequency oscillation curves of the synchronous generator are divided into four intervals; Figure 6 The comparison curves show the angular frequency response of fixed-parameter VSG control and the dual-parameter adaptive control proposed in this invention under the same disturbance in a new energy transmission system. Figure 7 The active power response curves of the fixed-parameter VSG control and the dual-parameter adaptive control proposed in this invention are compared under the same disturbance in a new energy transmission system. Figure 8 The curve showing the dynamic change of the damping coefficient in the dual-parameter adaptive control proposed in this invention; Figure 9 This is the dynamic change curve of the moment of inertia in the dual-parameter adaptive control proposed in this invention. Detailed Implementation

[0025] The present invention will now be described in detail with reference to the accompanying drawings and embodiments: like Figures 1 to 9 As shown, an adaptive control method for grid-type energy storage parameters to improve transient stability includes the following steps: A. Determine the rated angular frequency of the grid-type energy storage system, and simultaneously measure the current operating angular frequency to calculate the angular frequency deviation and angular frequency change rate; B. Measure the active power output of the VSG and calculate the active power deviation by combining it with the mechanical power command value; C. Based on the synchronous generator's power angle curve and frequency oscillation characteristics, the system oscillation period is divided into four oscillation intervals; D. Calculate the reference values ​​for damping coefficient and moment of inertia using the maximum mechanical torque of the VSG system, the maximum allowable angular frequency offset of the system, and the maximum active power output of the system; E. Based on the oscillation range determined in step C, and in conjunction with the adjustment coefficient, calculate the real-time moment of inertia and damping coefficient; F. Adjust the rotational inertia and damping coefficient of the VSG control.

[0026] Step A determines the rated angular frequency of the grid-type energy storage system, and simultaneously measures the current operating angular frequency, calculating the angular frequency deviation and the rate of change of angular frequency. The specific process is as follows: First, the rated angular frequency of the grid-type energy storage system is Simultaneously measure the current operating angular frequency. ; Then, calculate the angular frequency deviation. and rate of change of angular frequency ,as follows: .

[0027] Step B measures the active power output of the VSG and calculates the active power deviation by combining it with the mechanical power command value. The specific process is as follows: Measure the active power output of the VSG Combined with mechanical power command value Calculate the active power deviation ,as follows: .

[0028] Step C, based on the synchronous generator's power angle curve and frequency oscillation characteristics, divides the system oscillation period into four oscillation intervals. The specific process is as follows: Firstly, in interval number ①, the active power deviation Greater than zero, angular frequency deviation Greater than zero, rate of change of angular frequency Greater than zero; Secondly, in interval number ②, the active power deviation Less than zero, angular frequency deviation Greater than zero, rate of change of angular frequency Less than zero; Thirdly, in interval number ③, the active power deviation Less than zero, angular frequency deviation Less than zero, rate of change of angular frequency Less than zero; Fourth, in interval number ④, the active power deviation Greater than zero, angular frequency deviation Less than zero, rate of change of angular frequency Greater than zero.

[0029] Step D uses the maximum mechanical torque of the VSG system, the maximum allowable angular frequency offset of the system, and the maximum active power output of the system to calculate the reference values ​​for the damping coefficient and the moment of inertia. The specific process is as follows: First, the maximum mechanical torque of the VSG system is The maximum allowable angular frequency offset of the system is The maximum active power output by the system is ; Then, calculate the reference value of the damping coefficient. and the reference value of rotational inertia ,as follows: .

[0030] Step E calculates the real-time moment of inertia and damping coefficient based on the oscillation range determined in Step C and the adjustment coefficient. The specific process is as follows: First, the oscillation intervals defined in step C are obtained. , and This is the adjustment coefficient; Then, calculate the real-time moment of inertia. and damping coefficient ,as follows: .

[0031] Step F involves adjusting the rotational inertia and damping coefficient of the VSG control system. The specific process is as follows: Under the proposed control method, the system angular frequency and output active power satisfy the following equation: .

[0032] The adaptive control method for grid-type energy storage parameters is applicable to grid-type energy storage systems in isolated microgrids, grid-connected microgrids, and new energy power plants.

[0033] Mechanical power command value in step B The given value can be directly input as a target reference value for active power control of the VSG in a grid-type energy storage system.

[0034] Specifically, the rated angular frequency in step A Usually taken ,correspond The system can also be set according to the actual power grid frequency.

[0035] Specifically, the division of the oscillation interval in step C is based on the slope change and extreme points of the synchronous generator angular frequency curve.

[0036] Specifically, the maximum allowable angular frequency offset in step D is typically 1% to 3% of the rated value.

[0037] Specifically, in step E, to ensure the effectiveness of the damping effect while avoiding excessive damping that leads to a sluggish response, the damping adjustment coefficient is... Should meet: .

[0038] Specifically, the adjustment coefficient The calculation method for the lower limit of the value is as follows: Considering the smoothness of parameter adjustment and to avoid secondary oscillations in the system, it is derived from the distribution characteristics of the roots of the characteristic equation, combined with the stability conditions of the rotor motion equation.

[0039] The adjustment coefficient The calculation method for the upper limit of the value is as follows: In order to ensure the speed of dynamic response and avoid response sluggishness caused by over-adjustment, it is determined in combination with the overshoot and settling time requirements of the second-order system.

[0040] The range of values ​​for the adjustment coefficient can be appropriately expanded under the following circumstances: the grid-type energy storage system has sufficient reserve capacity and the requirement for transient stability is higher than that for dynamic response speed. Example

[0041] A grid-connected system model consisting of a synchronous machine, a wind turbine, and a VSG-controlled energy storage unit was built in MATLAB / Simulink. Its circuit model and simplified circuit are shown below. Figure 3 , Figure 4 As shown. The grid-type energy storage system employs the dual-parameter adaptive control method proposed in this invention, while the control group uses fixed-parameter VSG control (…). , The system parameter settings are shown in the table below:

[0042] The system is designed to incorporate a large load disturbance at 4 seconds.

[0043] Regardless of whether the system is in a steady state or under disturbance, the measuring device continuously acquires angular frequency data in real time. and output active power And, combining the known information, calculate the parameters using the following formula:

[0044] The calculation results determine the current oscillation range, and the corresponding parameter adjustment formula is called.

[0045] Simulation results of the angular frequency response of the two control methods under the same disturbance are as follows: Figure 6 As shown, under fixed-parameter VSG control, after load disturbance, the angular frequency drops rapidly, reaching a minimum of 311.5 rad / s, deviating from the rated value by about 1%. Subsequently, the fluctuation amplitude is large, and the recovery time to steady state is relatively long.

[0046] Under the dual-parameter adaptive control proposed in this invention, the disturbance instantaneously... A short-term increase, simulating inertial support, reduces the frequency drop, reaching a minimum of approximately 313 rad / s, a deviation of 0.3%, thus buffering the frequency abrupt change during the recovery phase. DDynamically increase, enhance damping, The subsequent fluctuation is less than 0.5 rad / s, improving frequency stability.

[0047] The active power response comparison results are as follows: Figure 7 As shown. Under fixed parameter control, the peak energy storage power is approximately 300MW after a disturbance, but because... J, D Fixed, lagging regulation leads to negative power and exacerbates system fluctuations. With adaptive control, disturbances are instantaneously mitigated due to... J As the system grows, more power is needed to support inertia. Energy storage provides the increased power to the system, with a peak power of approximately 450MW. This helps maintain system frequency stability, rapidly reduces fluctuations, and eliminates negative power. The power is then reduced to zero, and the adjustment is smooth. D Adaptive oscillation suppression, optimized power allocation, and reduced ineffective fluctuations.

[0048] Figure 8 and Figure 9 Damping coefficient D and moment of inertia J The change curve. Before the disturbance. Normal operation, after disturbance D Rising to 1100, strong damping suppresses oscillations. It falls back to 500, achieving strong damping during disturbances and weak damping in steady state. Before the disturbance... Normal operation, during disturbance J The frequency jumps to 240, with a short-term high-inertia buffer frequency abrupt change. The value drops back to 10 to avoid adjustment lag caused by long-term high inertia, achieve short-term inertia support, and maintain normal low inertia operation.

[0049] In summary, the simulation results fully verify the correctness and effectiveness of the present invention. Compared with fixed-parameter VSG control, the dual-parameter adaptive control proposed in this invention can significantly improve the transient stability of grid-type energy storage systems, effectively suppress frequency overshoot, accelerate convergence, and suppress oscillations.

[0050] Thus, the task of proposing an adaptive control method for grid-type energy storage parameters to improve transient stability, as proposed in this invention, has been fully completed.

[0051] This invention, starting from the rotor motion equations of a virtual synchronous generator, proposes a control method that dynamically adjusts the moment of inertia and damping coefficient by dividing the oscillation interval in real time. By utilizing local operating information such as actual measured angular frequency, actual measured output active power, rated angular frequency, and initial active power command value, combined with the synchronous generator's power angle characteristics and frequency oscillation patterns, this invention employs differentiated parameter adjustment strategies in different intervals—increasing the rate of change of inertia during frequency abrupt changes and increasing damping to accelerate convergence during oscillation decay, thus achieving synergistic optimization of transient stability and dynamic response. Furthermore, the adjustment coefficients proposed in this invention can be flexibly set according to system requirements, enabling grid-type energy storage systems of different capacities to undertake adjustment tasks proportionally, improving the coordinated control effect of multi-machine systems. This invention utilizes local information to achieve adaptive adjustment, resulting in fast control response, strong anti-interference capability, and adaptability to the large-scale application requirements of grid-type energy storage systems.

[0052] This invention pertains to a method for dual-parameter coordinated adjustment in virtual synchronous generator control. Its core advantage lies in overcoming the performance bottleneck of traditional fixed-parameter control, achieving a fusion of dynamic response speed and transient stability. It features fast dynamic response, high transient stability, and does not rely on communication systems, thus adapting to the development requirements of new energy power systems. When the system is subjected to small disturbances, parameter changes are gradual, avoiding over-adjustment; when severe disturbances occur, parameters are rapidly adjusted to suppress frequency abrupt changes. Simultaneously, the interval division rule proposed in this invention makes parameter adjustment more targeted, optimizing the effects of inertia and damping at different oscillation stages. This invention solves the deficiency in traditional virtual synchronous generator control where fixed parameters struggle to balance transient stability and dynamic response, significantly reducing frequency overshoot and shortening recovery time.

Claims

1. An adaptive control method for parameters of a grid-type energy storage system to improve transient stability, characterized in that: Includes the following steps: A. Determine the rated angular frequency of the grid-type energy storage system, and simultaneously measure the current operating angular frequency to calculate the angular frequency deviation and angular frequency change rate; B. Measure the active power output of the VSG and calculate the active power deviation by combining it with the mechanical power command value; C. Based on the synchronous generator's power angle curve and frequency oscillation characteristics, the system oscillation period is divided into four oscillation intervals; D. Calculate the reference values ​​for damping coefficient and moment of inertia using the maximum mechanical torque of the VSG system, the maximum allowable angular frequency offset of the system, and the maximum active power output of the system; E. Based on the oscillation range determined in step C, and in conjunction with the adjustment coefficient, calculate the real-time moment of inertia and damping coefficient; F. Adjust the rotational inertia and damping coefficient of the VSG control.

2. The adaptive control method for grid-type energy storage parameters to improve transient stability according to claim 1, characterized in that: Step A determines the rated angular frequency of the grid-type energy storage system, and simultaneously measures the current operating angular frequency, calculating the angular frequency deviation and the rate of change of angular frequency. The specific process is as follows: First, the rated angular frequency of the grid-type energy storage system is Simultaneously measure the current operating angular frequency. ; Then, calculate the angular frequency deviation. and rate of change of angular frequency ,as follows: 。 3. The adaptive control method for grid-type energy storage parameters to improve transient stability according to claim 1, characterized in that: Step B measures the active power output of the VSG and calculates the active power deviation by combining it with the mechanical power command value. The specific process is as follows: Measure the active power output of the VSG Combined with mechanical power command value Calculate the active power deviation ,as follows: 。 4. The adaptive control method for grid-type energy storage parameters to improve transient stability according to claim 1, characterized in that: Step C, based on the synchronous generator's power angle curve and frequency oscillation characteristics, divides the system oscillation period into four oscillation intervals. The specific process is as follows: Firstly, in interval number ①, the active power deviation Greater than zero, angular frequency deviation Greater than zero, rate of change of angular frequency Greater than zero; Secondly, in interval number ②, the active power deviation Less than zero, angular frequency deviation Greater than zero, rate of change of angular frequency Less than zero; Thirdly, in interval number ③, the active power deviation Less than zero, angular frequency deviation Less than zero, rate of change of angular frequency Less than zero; Fourth, in interval number ④, the active power deviation Greater than zero, angular frequency deviation Less than zero, rate of change of angular frequency Greater than zero.

5. The adaptive control method for grid-type energy storage parameters to improve transient stability according to claim 1, characterized in that: Step D uses the maximum mechanical torque of the VSG system, the maximum allowable angular frequency offset of the system, and the maximum active power output of the system to calculate the reference values ​​for the damping coefficient and the moment of inertia. The specific process is as follows: First, the maximum mechanical torque of the VSG system is The maximum allowable angular frequency offset of the system is The maximum active power output by the system is ; Then, calculate the reference value of the damping coefficient. and the reference value of moment of inertia ,as follows: 。 6. The adaptive control method for grid-type energy storage parameters to improve transient stability according to claim 1, characterized in that: Step E calculates the real-time moment of inertia and damping coefficient based on the oscillation range determined in Step C and the adjustment coefficient. The specific process is as follows: First, the oscillation intervals defined in step C are obtained. , and This is the adjustment coefficient; Then, calculate the real-time moment of inertia. and damping coefficient ,as follows: 。 7. The adaptive control method for grid-type energy storage parameters to improve transient stability according to claim 1, characterized in that: Step F involves adjusting the rotational inertia and damping coefficient of the VSG control system. The specific process is as follows: Under the proposed control method, the system angular frequency and output active power satisfy the following equation: 。 8. The adaptive control method for grid-type energy storage parameters to improve transient stability according to claim 1, characterized in that: The adaptive control method for grid-type energy storage parameters is applicable to grid-type energy storage systems in isolated microgrids, grid-connected microgrids, and new energy power plants.

9. The adaptive control method for grid-type energy storage parameters to improve transient stability according to claim 1, characterized in that: Mechanical power command value in step B The given value can be directly input as a target reference value for active power control of the VSG in a grid-type energy storage system.

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